Implementing a Participatory Model of Micro Health Insurance among Rural Poor with Evidence from...

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The Geneva Papers, 2014, 00, (124) © 2014 The International Association for the Study of Insurance Economics 1018-5895/2014 www.genevaassociation.org Implementing a Participatory Model of Micro Health Insurance among Rural Poor with Evidence from Nepal David M. Dror a,b , Atanu Majumdar a , Pradeep Panda a , Denny John a and Ruth Koren c a Micro Insurance Academy, 52B Okhla Industrial Estate, Phase-3, New Delhi 110020, India. b Erasmus University Rotterdam, Institute of Health Policy and Management, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands. E-mail: [email protected] c Tel Aviv University, Felsenstein Medical Research Center, Sackler Faculty of Medicine, Ramat Aviv, Tel Aviv, Israel. This paper reports on two voluntary, contributory, contextualised, community-based health insurance (CBHI) schemes, launched in Dhading and Banke (Nepal) in 2011. The implementation followed a four-stage process: initiating (baseline survey), involving (awareness generation and engaging community in benet-package-design), launch (enrolment and training of selected community members) and post-launch (viable claims ratio, settled within satisfactory time, sus- tainable afliation). Both schemes were successful on four key parameters: effective planning; afliation (grew from 0 to ~10,000) and renewals (>65 per cent); claims ratio (~50 per cent); and promptness of claim settlement (~23 days). This model succeeded in implementing CBHI with zero premium subsidies or subsidised health-care costs. The successful operation relied in large part on the fact that members trust that they can enforce this contract. Considerable insurance education and capacity development is necessary before the launch of the CBHI, and for sustain- able operations as well as for scaling. The Geneva Papers (2014) 0, 124. doi:10.1057/gpp.2013.31 Keywords: Nepal; micro health insurance; community-based health scheme; benet package design; health insurance performance indicators; microinsurance implementation process Article submitted 8 May 2013; accepted 15 October 2013; advance online publication, 15 January 2014 The online version of this article is available Open Access Introduction In countries where governments can neither mandate contributory universal health coverage (UHC) nor subsidise its full cost, one of the great challenges is reducing private out-of- pocket expenditure (OPE) for health care payable at the point and time of service. This inequitable and inefcient health nancing mechanism 1 persists in many low-income countries. 2 In Nepal, the third poorest country in Asia, OPE represents around 72 per cent 1 Garg and Karan (2009). 2 Xu et al. (2010).

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The Geneva Papers, 2014, 00, (1–24)© 2014 The International Association for the Study of Insurance Economics 1018-5895/2014

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Implementing a Participatory Model of Micro HealthInsurance among Rural Poor with Evidence fromNepalDavid M. Drora,b, Atanu Majumdara, Pradeep Pandaa, Denny Johna and RuthKorencaMicro Insurance Academy, 52B Okhla Industrial Estate, Phase-3, New Delhi 110020, India.bErasmus University Rotterdam, Institute of Health Policy and Management, P.O. Box 1738, 3000 DR Rotterdam,The Netherlands.E-mail: [email protected] Aviv University, Felsenstein Medical Research Center, Sackler Faculty of Medicine, Ramat Aviv, Tel Aviv,Israel.

This paper reports on two voluntary, contributory, contextualised, community-based healthinsurance (CBHI) schemes, launched in Dhading and Banke (Nepal) in 2011. The implementationfollowed a four-stage process: initiating (baseline survey), involving (awareness generation andengaging community in benefit-package-design), launch (enrolment and training of selectedcommunity members) and post-launch (viable claims ratio, settled within satisfactory time, sus-tainable affiliation). Both schemes were successful on four key parameters: effective planning;affiliation (grew from 0 to ~10,000) and renewals (>65 per cent); claims ratio (~50 per cent); andpromptness of claim settlement (~23 days). This model succeeded in implementing CBHI withzero premium subsidies or subsidised health-care costs. The successful operation relied in largepart on the fact that members trust that they can enforce this contract. Considerable insuranceeducation and capacity development is necessary before the launch of the CBHI, and for sustain-able operations as well as for scaling.The Geneva Papers (2014) 0, 1–24. doi:10.1057/gpp.2013.31

Keywords: Nepal; micro health insurance; community-based health scheme; benefit packagedesign; health insurance performance indicators; microinsurance implementation process

Article submitted 8 May 2013; accepted 15 October 2013; advance online publication,15 January 2014

The online version of this article is available Open Access

Introduction

In countries where governments can neither mandate contributory universal health coverage(UHC) nor subsidise its full cost, one of the great challenges is reducing private out-of-pocket expenditure (OPE) for health care payable at the point and time of service. Thisinequitable and inefficient health financing mechanism1 persists in many low-incomecountries.2 In Nepal, the third poorest country in Asia, OPE represents around 72 per cent

1 Garg and Karan (2009).2 Xu et al. (2010).

of total health-care costs.3 The World Health Organization proposes the introduction ofprepayment and risk pooling as a way to solve this problem.4 Several experiments withcommunity-based health insurance (CBHI) have been reported5,6,7; in Nepal, experimentswith CBHI have been carried out since 2004, both in rural and in urban settings.8,9 Mostprojects depended on external subsidies and offered provider-based health insurance witha restricted choice of health-care services. Recently, the Government of Nepal has showninterest in universal health care (UHC) through implementation of health insurance10;however, it has neither launched a national scheme nor entered into arrangements withcommercial insurers to secure an ample supply of health insurance, notably in difficult-to-reach locations. Rather, it has designated several “pilot” districts for experimentation withseveral models, notably CBHI. This paper addresses the question whether and how it ispossible to operate sustainable health insurance in the informal sector in rural Nepal withoutpremium subsidies, and what useful role communities can play in the self-governance oftheir insurance.We present here the voluntary and contributory CBHI model that has been piloted in

Nepal. The empirical scope covers CBHI operations from 2011 until 2013. The novelty ofthis implementation model is its combination of high-resolution data collection and analysis,reliance on revenue generation on a voluntary basis rather than on premium subsidies, andcapacity development. The conceptual framework of this model includes tailoring benefits tolocal risks at premiums perceived locally as affordable; involving prospective beneficiariesin benefit package design to ensure that their perceived priorities are given voice; assigningresponsibility for governance of the schemes to members, to reduce conflicts of interests andenhance the likelihood that benefits are paid as promised; and localising operations of thescheme at community level with suitable capacity development.The paper is structured as follows: we provide details on the location, data and methods used

in this study, followed by a description of the implementation model. The findings, reflectingthe experience during two full years of operation using established performance indicators,follow. We interpret the findings in the discussion section, and end by formulating conclusions,notably on sustainability and scalability of this CBHI implementation model, and its potentialcontribution to achieving the social policy goals of the Government of Nepal.

Data and methods

The CBHI schemes studied

This paper describes the implementation of two schemes: Saubhagya, launched in January2011 in Dhading district by a consortium composed of Development Project Service Centre

3 World Bank (2007).4 World Health Organization (2011).5 Biener and Eling (2012).6 Mahal et al. (2013).7 Borghi et al. (2013).8 GIZ Health Sector Support Program, Department of Health Services (2012).9 Stoermer (2012).10

“National Health Insurance Policy 2012” of the Government of Nepal.

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(DEPROSC),11 Micro Insurance Academy (MIA)12 and Save the Children Nepal (STC).13

Sanjeevni was launched in June 2011 in Banke district by a consortium composed ofNirdhan Utthan Bank (Nirdhan),14 MIA and STC.

Data sources

This paper is based on three data sources.

A baseline studyConducted from January to April 2009, it included a household survey, focus groupdiscussions (FGDs) and key informant interviews15 to gather information on socio-economicand demographic features, health-seeking patterns and how the local population financedaccess to health care. A two-stage sampling method was applied. The first entailed purposiveselection of “village development committees” (VDC) and wards (administrative divisionssmaller than districts) to include the places the field partners designated for implementationof the CBHI schemes. The second stage included selection of intervention and controlgroups; the intervention groups included those to whom the CBHI was going to be offered(often organised as “self-reliant groups” (SRG) numbering about 15–20 people who wereaffiliated with DEPROSC in Dhading and with Nirdhan in Banke)16; the control groups, ofequal size, were not invited to join. We call these sub-cohorts “members” and “non-members”, respectively.The sample consisted of 1,000 households from Dhading and 1,008 households from

Banke. The sample size was calculated based on an error margin of 0.005 (for estimationof the hospitalisation rate with a prior estimated value of 0.04), a confidence interval of80 per cent and a design effect of 2.17 We interviewed a members sample comprised of504 households randomly sampled from 17 VDCs in Banke (from Nirdhan’s list), respectinga proportional number of members in the local ward population (member strength in Wardto member strength in VDC)18; and a random sample of 500 households in Dhading fromthe list of DEPROSC members (covering nine VDCs).19 The non-members were selectedrandomly in each village, following the “four winds” method.20

For the purpose of analysis of the results of the implementation, only members’ householdbaseline data are used.

11 http://www.deprosc.org.np/Home.aspx12 http://www.microinsuranceacademy.org/13 http://www.savethechildren.org/site/c.8rKLIXMGIpI4E/b.6150545/k.B8DE/Nepal.htm14 http://www.nirdhan.com/15 Dror and Radermacher (2010).16 An SRG is a group of 10–15 women who agree to deposit a fixed amount every month in a common kitty.

When a member is in need of money, she can borrow the amount from the common kitty. She pays a servicecharge (equivalent to interest) to the group fund. Each SRG has a bank account in the name of the group.

17 Cochran (1977).18 With the following breakdown by VDC: 99 households in Bageswari, 33 in Banratuwa, 4 in Belbhar, 28 in

Chisapani, 12 in Indrapur, 3 in Jaispur, 6 in Khajurapur, 124 in Kohalpur, 24 in Manikapur, 26 in Navabasta,18 in Paraspur, 12 in Rajapur, 63 in Rajhaina, 10 in Sahigaon, 5 in Samserganj, 20 in Sitapur and 17 in Titanaria.

19 Breakdown by VDCs was follows: 98 households in Baireni, 12 in Benighat, 21 in Bhumesthan, 21 in Dhusha,43 in Gajuri, 86 in Jogimara, 42 in Kalleri, 70 in Kumpur, and 107 in Pida.

20 Som (1996).

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The average monthly per capita consumption (MPCC) of the members sub-cohorts asper the baseline was Napalese rupees (NPR) 2,402 ±77.6 (= purchasing power parity (PPP)$ 82±2.65) at Dhading and NPR 1,979 ±58.2 (= PPP$ 68±1.99) at Banke.21 Estimatedliteracy rates of members sub-cohorts at Dhading and Banke were 81 and 82 per cent,respectively. The female literacy rate was 75 per cent in both places. The average family sizewas 5.63 (±0.08) in Banke and 5.24 (±0.06) in Dhading. In all, 29 per cent of houses inBanke were permanent housing structures (“pacca houses”), compared with only 13 per centin Dhading (Table 1).

Results of simulations at the design phaseDuring the preparatory stage, a series of simulation exercises were conducted with groups(each of about 15 SRG members) to obtain data on the benefits and compositions that mightsuit best. The results of these simulation exercises were recorded and served as one datasource at various stages of the implementation process.

Actual results of the schemesData was obtained from the books of accounts (e.g. number of paid-up members, premiumscollected and payments made to members) and operational records of the CBHI schemes(notably information on number of claims, time needed to process those claims and numberof meetings of the claims committees).

Essentials of the implementation model

The business process of implementation of this CBHI model follows four consecutive stages(see Appendix A).

Initiating: Initiating refers to the preparatory stage in which success implies the garnering ofadequate information—on local willingness to pay, incidence of illness and costs—neededfor provision of sound actuarial and other technical advice. In Nepal this information wasgathered through the baseline study conducted in 2009.

Table 1 Socio-demographic profile of respondents

Dhading Banke

MPCC (NPR) 2402± 77.6 1979± 58.2MPCC (PPP$) 82± 2.65 68± 1.99Total literacy 81% 82%Female literacy 75% 75%Average family size 5.24± 0.06 5.63± 0.08House type (permanent structure) 13% 29%Predominant religion Hindu HinduPredominant language Nepali Nepali

21 Conversion rate PPP$ 1=NPR 29.25, in year 2009. The per capita per month GNI of Nepal was estimated at100 PPP$ for the year 2009.

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Involving: Involving refers to the stage in which success implies that the target groups areable to form consensus on the design and pricing of the benefit package for their community,pursuant to participation in awareness and capacity-building activities. This was done in2010.Launch: Launch refers to the stage in which success implies two things: that CBHI memberschoose some members to be the office-bearers to manage and govern the scheme, and thatenrolments reflect the community’s consensus that insurance (through the customised benefitpackage) is better than no insurance.Post-launch: Post-launch refers to the stage in which success implies that the loss ratio isviable, that claims are settled in a contextually satisfactory time frame, that the income frommembership (new and renewals) is adequate to fund sustained operations, that communityconsensus on the benefit package extends into subsequent years, and that the CBHI has thecapacity to satisfy the community’s ongoing technical support needs.At the Initiating stage, the target community agrees to cooperate with an external body

in surveying local conditions of risk exposure and perceptions of priorities aboutrisk. Unremunerated interviewees share information; they expect a return, which (in thisimplementation model) is a promise to propose the insurance that could improve theirlives. This engagement with the external organisers establishes agreed roles: the expertcollects data and offers knowledge-based recommendations and the community decides onthe action. Stated differently, the external expert (in this case the Micro InsuranceAcademy—MIA) acts as “change maker” and the local community acts as “decision-maker”. The decisions are taken during the Involving stage, when the target group isengaged in benefit package design. The package that communities can compose may differradically from anything offered by an insurer (if any offer exists at all). The assumptionunderlying this stage of the process is that, when prospective enrollees can participate incomposing the package that reflects their perceived priorities, they will be more willing toaffiliate and to pay. For as long as there is no willingness to pay (WTP), there can be nodemand; asserting needs without solvent demand leads nowhere, and the necessarycondition towards expanding health insurance coverage is that solvent demand existswhere none existed before. The essential success of Involving is when the target groupreaches consensus that being health-insured is “what we all do”, at a price that we all arewilling to pay. This also means that Involving is essentially a group decision rather than anindividual choice.Had there been ample competition in the supply of health insurance, the community could

have shopped around for the package and price they wanted. But, the supply of insurance tothe informal sector in Nepal is insufficient, both in terms of coverage and in terms ofpremium competition. Therefore, the Launch stage includes a decision by the community toact as “market maker” for the benefit package chosen by its members at the price they arewilling to pay. As the community now needs the skills required to operate the scheme, theassistance must include a “competence chain” through which local persons are trained inskills they need to operate the insurance. The key roles are briefly described next.The “insurance activists” (IAs) are the first line of managing the CBHI scheme; they move

from village to village and door to door to enrol members, maintain direct contact withmembers, provide information, collect premiums, assist members to avail services (e.g.guide to certain health-care providers) and in submitting claims, etc. In Dhading each of thesix IAs covers 150 members, while in Banke, each of the five IAs covers 455 members.

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This large gap in member per IA reflects the time/effort required to reach the members intheir villages in very different terrains. The IAs are employed by the CBHI and draw amonthly payment.Another role is that of “insurance coordinator” (IC) who keeps membership records and

books of accounts using a management information system provided by MIA, manages thebank account, and may also maintain relationships with health-care providers. From 2011onwards, one IC was employed in Dhading and two in Banke.Claims for reimbursement are adjudicated by the “Claims Committee” (CC). The CC is

composed of one representative from each VDC where the members live, designated/electedby the “self-reliant groups” to sit on the CC. Candidates must be literate, understand theclaims process and be able to make decisions promptly. In Dhading, seven CCs with 42members were active in 2011, and eight CCs comprising 49 members in 2012, and theincrease in 2012 was occasioned by the addition of two VDC populations; in Banke therewere five CCs with seven members each operating in 2011 and in 2012. CC members meetonce a month and receive a “sitting fee”.Finally, the “Coordination Committee” (CoCo) supervises the overall financial perfor-

mance of the scheme. The CoCo meets monthly; reviews the financial performance; signschecks, policy documents and claim overview documents22; conducts client disputeresolution, etc. In Dhading there was one CoCo, with seven members in 2011 and eightmembers in 2012. In Banke (where the CoCo is called “Main Committee”), one committeeoperated with seven members in 2011 and 2012. CoCo members are paid a sitting fee by thescheme.

Results

The results of the Nepali CBHI schemes are examined here against nine pieces of essentialinformation, some of which follow accepted performance indicators.23

Willingness to pay

Before launching a new CBHI, it is essential to have an estimate of WTP for health insuranceamong the target group (especially when the expected income from premium subsidies iszero) because WTP is used as a proxy for premiums that define the limits of the benefitpackage. The baseline survey includes elicitation of WTP. There are several methods toobtain this estimate24; we used the descending bidding game method,25 which consisted ofasking each interviewee how much she/he would agree to pay for health insurance thatwould cover part of the cost of their health care on the basis that, if you are willing to paymore, you will get more benefits and, if you are willing to pay less, you will get fewer

22 The claim overview document is a document generated by the MIS application following submission of a claim.The system validates the claim amount under different benefit heads and calculates the amount payable basedon the amount already received by the claimant. This calculation helps the CoCo to verify that decisions on theclaim taken by the CC are fine.

23 Wipf and Garand (2010).24 Dror and Koren (2012).25 Dror et al. (2007).

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benefits. The opening bid (of NPR 30 per person per month)26 was intended to be refused astoo high; when a bid was refused, a lower bid (1 NPR less) was offered, repeatedly, until abid was accepted or the bid reached NPR 0. The accepted bid was recorded as therespondent’s WTP. The median WTP was NPR 10.0 in Dhading and NPR 10.5 in Banke.All results of the bidding game are shown in Figures 1 and 2.We also considered another method to estimate WTP, based on mean food expenditure.27

The advantage of this method is that it bases the estimate of WTP on actual costs of knowngoods, rather than on unknown costs of uncertain services. By applying this method inNepal, the first approximation of WTP was NPR 41±1 in Dhading and NPR 38±1 in Banke(about 4.5 per cent of mean food expenditure of the target population).These two estimates of WTP, though markedly different, are taken as the lower and upper

boundaries of scheme revenues within which the benefit package can be designed.

Benefit package design and pricing

It is known that benefit package design is an exercise in rationing limited resources.28 Twokey issues underlie this rationing exercise: firstly, the benefits must reflect local health needs

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Figure 2. Results of the bidding game for WTP, Sanjeevni Banke.

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Figure 1. Results of the bidding game for WTP, Saubhagya Dhading.

26 An indicative exchange rate is 100 NPR=1 USD.27 Binnendijk et al. (2013).28 Ryan et al. (2001).

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and local availability of health services; secondly, the people in the target population mustagree to the rationing decisions, as they can refuse enrolment, which is voluntary.We apply a modified version of a preference elicitation method called CHAT (Choosing

Healthplans All Together) that has been successfully applied in many locations in ruralIndia.25,29 In the first stage of the process (known as the design workshop stage), thecommunity (through its representatives) is shown many benefit package options, each with aparticular premium. Through an iterative process of deliberations, the participants select fourto five options that match the needs and WTP of the community. It is noted that the pricereflects pure actuarial premiums plus about 30 per cent to cover risk loading andadministrative expenses (incurred by the community in running the scheme), but withoutprofit or any other cost (and no payment to MIA). The four or five benefit package optionsselected in the design workshop are then disseminated in the community (through pictorialpaper boards called CHAT Boards; the CHAT board used in 2011 is attached as Appendix Bfor illustration), for discussion and decision. The package selected by the largest number ofgroups is retained for the entire scheme. A total of 47 such group discussions took place inDhading and 81 in Banke. The CHAT and benefit/premium selection process is repeatedeach year, to allow the communities to adjust their priorities based on experience, and toincrease coverage when WTP increases. Prior to preparation of new CHAT boards for 2012,a series of 24 FGDs were conducted in Dhading in June 2012 to elicit opinions on changes inthe benefits and premiums for the next year. These FGDs led to proposals30 which wereconsidered during the “redesign workshop” by community representatives (CC and CoComembers). The CHAT exercises were administered among enrolled members and amongnon-members, with the view to enrolling more members.The package options (those considered and those retained) for 2011 and 2012 are shown

in Table 2.Involving people in the CHAT exercises is a hands-on demonstration of the interplay

between premiums on the one hand, and the width of benefits and depth of coverage, on theother. This experience helps manage expectations to realistic dimensions and minimisesdisappointments with reimbursements.The premium levels that were chosen by the groups were within the estimated range

of WTP (i.e. between NPR 10 and NPR 41±1 in Dhading, and between NPR 10.5 andNPR 38±1 in Banke) and closer to the higher limits.As for the package design, the choices clearly favoured broad packages that included both

outpatient and inpatient coverage. However, the cost of covering medicines was too high tobe retained. The apparent trade-off was to choose a lower cap for hospital reimbursements.It is also interesting to note that the benefit choices in Dhading and Banke were different

from each other in Year 1 and converged towards more similarity in Year 2.Based on the CHAT choices, the schemes implemented the packages described in

Table 3.It is noteworthy that the Dhading scheme changed the method of calculating caps,

from a cap per person per year (pppy) to a dual cap per event (p.e.) and per family per year

29 Danis et al. (2007).30 For example, in Dhading in 2012, the community mentioned injury to be a part of the benefit package, and later

a survey among 455 members was conducted to calculate the probability and cost of injury.

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Table 2 Benefit package options and premiums—including final selection per year per community (in Nepalese rupees)

Benefit options Dhading Banke

2011 2012 2011 2012

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4

Hospitalisation 5,000 4,000 5,000 6,000 4,000 2,500 3,000 4,000 5,000 2,500 2,000 4,000 5,000 4,000 5,000 2,500 4,000 3,000 2,000Imaging 500 400 500 400 600 700 600 400 250 500 1,000 1,000 1,000 300 250 400 600Lab tests 600 250 400 250 250 400 500 400 250 200 250 250 500 1,000 200 200 250 400Transport 200 400 300 200 100 100 200 200 200 200Wage loss @100/d @100/dMedicines 500Premium PPPMa 23.1 24.5 24.7 25.4 26.2 21.1 28 31.7 34.3 76.4 20 30.3 35.1 36.1 38.8 28.3 33.3 33.8 35Groups chose this 3/47 0 7/47 0 37/47 7/91 78/91 1/91 2/91 3/91 40/81 5/ 81 0 4/81 32/81 9/180 7/180 1/180 163/180% of group choices 6% 0% 15% 0% 79% 8% 86% 1% 2% 3% 49% 6% 0% 5% 40% 5% 4% 1% 90%Final selection ✓ ✓ ✓ ✓

aPer person per month: During the CHAT, the premiums paid per month are shown to the community for the purpose of simplicity.

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(pfpy). This method of calculating the benefit, called “family floater”,31 increases thecoverage amount available to sick individuals within a family unit; yet, there is no evidencethus far of adverse selection, with the notable exception that family size of the insured issmaller than expected, when larger family size could have been expected. One lesson mightbe to link the application of the family floater with an obligation to affiliate entire families,which could reduce the financial risk for the scheme and enhance the inclusive natureof the scheme.

Membership in the CBHI

Enrolment into the schemes was open during “affiliation periods” lasting two months;enrolment was not possible outside these affiliation periods. The evolution of membershipnumbers until 31 January 2013 is shown in Table 4.Overall, membership numbers doubled from Year 1 (2011) to Year 2 (2012), with

satisfactory renewal rates in Dhading, and relatively lower rates in Banke.

Table 3 The implemented benefits packages

Benefit type Conditions Year 1 Year 2

BankeSanjeevni

DhadingSaubhagya

BankeSanjeevni

DhadingSaubhagya

Hospitalisationbenefit

All hospitalisations >24 h covered; only fromselected hospitals: government and private; alldirect hospital costs covered; hospital bill +medicines needed and bought duringhospitalisation in pharmacy outside hospital +tests and imaging prescribed and done duringhospitalisation in testing centre outside hospital

pppya:NPR2,000

pppy: NPR4,000

pppy:NPR2,000

p.e.b:3,000;pfpy:20,000

Transportationbenefit

A one-time flat amount compensation fortransportation costs for all hospitalisations of atleast 24 h

NPR 100 NPR 400 NPR 200 NPR 300

Imaging testsbenefit

Imaging test prescribed by the doctors of selectedhospitals and done in an outpatient setting (notduring hospitalisation of more than 24 h)

pppy:NPR 250

pppy: NPR500

pppy:NPR 600

p.e.: NPR600; pfpyc:3,000

Lab testsbenefit

Lab tests prescribed by the doctors of selectedhospitals and done in an outpatient setting (notduring hospitalisation of more than 24 h)

pppy:NPR 200

pppy: NPR250

pppy:NPR 400

p.e.: NPR400; pfpy:3,000

apppy=maximum amount insurance will pay out per person per year.bp.e.=maximum amount insurance will pay per event.cpfpy=maximum amount insurance will pay out per family per year.

31 In a family floater policy, the cap limits total payout to the family, instead of an event or an individual. In casesomeone becomes sick multiple times, she/he can take advantage of the higher per family cover.

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Household size of the insured population

The mean household size of the members sub-cohort in the baseline survey was 5.24± 0.063in Dhading and 5.63±0.075 in Banke (data sourced from baseline survey). Surprisingly, theaverage household size of enrolled members was significantly lower, at 2.85±0.035 inDhading and 2.44±0.019 in Banke (obtained from membership records). This big differenceraises the question which demographic segment has been excluded by families.Table 5, providing the age and gender distributions of the two groups (the sampled

“member” sub-cohort in the household survey vs the actual CBHI membership), showsclearly that adult women are over-represented in the insured cohort, compared with men andwith their proportion in the overall population (household survey data). And, young girls areunder-represented among the insured, compared both with young boys and with their sharein the population.

Incidence of claims

We compare the expected and actual incidence of claims for the three main benefit typesthat formed the basis of members’ benefits premium package choice, based on two years’experience. The results are summarised in Table 6.The agreement between expected and actual incidence of hospital claims is very good in

Banke and in the second batch of affiliation in Dhading; the first batch of enrollees inDhading had lower incidence than expected, which may reflect that the number of enrolledwas too small to represent the target group correctly.As for imaging and lab claims, actual incidence was lower than expected in Banke, and

this could explain the decision of both schemes to increase the cap for this benefit in Year 2,to offset the lower incidence by higher reimbursement at a similar premium. This suggeststhat the insured understood the pricing mechanism very well. The agreement betweenexpected and observed number of claims suggests that adverse selection, moral hazard and

Table 4 Membership in the CBHIs

Enrolment period Enrolmentstatus

Total membersper scheme

Renewal % Totalproject

New Renew Total SaubhagyaDhading

SanjeevniBanke

SaubhagyaDhading

SanjeevniBanke

2011 January 514 514 514 5142011 June 4,176 4,176 4,6902011 July 394 394 908 5,0842012 January 1,066 349 1,415 1,809 67.9% 5,9852012 June 5,818 2,063 7,881 49.4% 9,6902012 July 391 254 645 2,060 64.5% 9,9412013 January 1,753 965 2,718 3,363 68.2% 11,24431 Dec. 2011 5,08431 Dec. 2012 9,94131 Jan. 2013 11,244

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Table 5 Age and gender distribution (“members” cohort in the household survey vs insured population)

Age Dhading baselinemembers sample

Dhadinginsured

Significance of differencegender ratio inHHS vs insured

Banke baselinemembers sample

Bankeinsured

Significance of differencegender ratio inHHS vs insured

Male Female Male Female p-value Male Female Male Female p-value

<6 11.7% 11.5% 13.3% 5.9% 0.000 9.6% 11.0% 16.6% 7.2% 0.0006–15 25.3% 25.1% 25.6% 15.2% 0.000 22.9% 23.3% 32.5% 14.1% 0.00015–59 56.5% 58.6% 55.4% 74.4% 0.000 61.8% 59.8% 46.7% 75.1% 0.00060 + 6.4% 4.8% 5.7% 4.4% 0.000 5.7% 5.9% 4.2% 3.5% 0.000Total 100% 100% 100% 100% 0.000 100% 100% 100% 100% 0.000n 1,699 1,269 1,377 1,381 NA 7,927 4,154 1,452 1,478 NA

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fraud seem to be in good control. This is an interesting observation, which may reflectcommunity governance of the scheme.

Cost of reimbursable claims

The actual costs paid by the CBHI schemes were compared with the expected costs that weresimulated by using the members cohort in the household data, applying identical insurancerules (results shown in Table 7).As can be seen, the actual and expected average costs per claim are remarkably similar,

even though, in three cases, the difference is significant (unpaired Student’s t-test). Theseresults confirm that it is possible to base the actuarial calculations underlying package designon the baseline data.

Loss ratio (a.k.a. claims ratio)

Loss ratio (i.e. the amount paid as benefits divided by the total premium income) is a measureof the financial stability of the scheme, providing an indication of the adequacy of premiumscharged relative to underwritten risk. The data shown (Table 8) refers to the first full yearfor which all claims were settled. The loss ratio is satisfactory and confirms that the twoschemes collected suitable premiums. Note that in Dhading, the loss ratio of the secondbatch of enrollees was 56.7 per cent, higher by about 40 per cent from the first batch (with40 per cent), but still within a very suitable range.

Table 6 Comparison between expected and actual incidence of claims

Incidencedistrict

Hospitalisations Imaging Lab tests

Actual(%)

Expected(%)

p-valuea Actual(%)

Expected(%)

p-valuea Actual(%)

Expected(%)

p-valuea

Dhading (January 2011) 2.1 3.7 0.225 13.4 15.9 0.484 10.5 18.5 0.001Dhading (July 2011) 3.3 3.7 0.934 18.3 15.9 0.587 10.9 18.5 0.006Banke (June 2011) 3.3 3.1 0.878 14.8 22.2 0.000 11.8 34.1 0.000

aChi-square test.

Table 7 Comparison between expected and actual cost of claims

Mean cost per claim(NPR)

Hospitalisations Imaging Lab

district Actual(paid)±SEMa

Expected±SEM

Actual±SEM

Expected±SEM

Actual±SEM

Expected±SEM

Dhading (January 2011) 3094± 356 3303± 106 332± 18 395± 25 198± 10 197± 10Dhading (July 2011) 3250± 302 3303± 106 313± 17 395± 25 217± 9 197± 10Banke (June 2011) 1665± 45 1853± 34 225± 2 228± 6 162± 5 161± 6

aSEM= standard error of the mean.

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Value for money

One way to express “value for money” for the insured is to look at the probability that theclaims submitted will be fully reimbursed. It is self-explanatory that the cap is designed tocurtail some costs, and the probability of full reimbursement increases as the cap increases,but so do the premiums. The outcomes were as follows: in Dhading, in 2011 (the first yearfor which all claims were settled), 48 per cent of hospitalisations were fully reimbursed; inBanke, the rate was 41 per cent. This coverage seems too low. The share of claims that wouldhave been fully paid at different levels of the cap, and the corresponding premiums areshown in Figures 3 and 4.As can be seen, a small increase in a low cap occasions relatively better coverage for a

modest premium increase, since the two lines in the graph are not parallel or linear (e.g. therange from 4,000 to 6,000 ≈ PPP$136.80 to PPP$205.10). For example, had the cap beenincreased from NPR 4,000 to NPR 5,000 in Dhading, 78 per cent of hospital claims wouldhave been fully covered, while the premium would have increased by only NPR 23 pppy(from NPR 123 to 146).In Dhading, some 89 per cent of imaging claims were fully covered with a cap of 500, and

in Banke, only 24 per cent were fully covered when the cap was 250. It is interesting to notethat both CBHI schemes chose a cap of 600 in 2012; this corrective choice seems suitable forBanke, but less necessary for Dhading. Finally, 45 per cent of lab claims in Dhading werefully covered (with a cap of 250), and 34 per cent in Banke (cap of 200). Both schemes choseto raise the cap to 400 in the following year. The involvement of communities in package

Table 8 Loss ratio (a.k.a. claims ratio) for the first year

Location No. ofinsured

Premium income(in NPR)

No. ofclaims

Claim amount(in NPR)

Lossratio (%)

Dhading (January 2011) 514 172,704 104 69,063 40.0Dhading (July 2011) 394 132,384 104 74,998 56.7Banke (June 2011) 4,177 1,052,352 810 461,830 43.9

0%

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40%

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120%

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% c

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Hospital Benefit at different caps (p.p.p.y)

Premium % claims fully covered

2000 4000 6000 80000 10000 12000 14000

Figure 3. Coverage levels at different caps/hospitalisations (Dhading).

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revision offered the opportunity to adjust perceived value for money and the resultinginterest to remain insured.

Members’ experience of the claims process

Of 810 claims submitted in Dhading, only four claims were rejected (less than half of 1 percent, due to client fraud or incomplete bills submitted by members). No claim rejections wereregistered in Banke.Another way of measuring the experience of insured persons is the time interval

between claim submission and reimbursement. We measured promptness in threedistinct ways: firstly, how long it took from submission to the IA until the claims weredecided by the CC; secondly, the delay from decision by the CC to actual payment tomembers; and thirdly, the promptness of the entire process from a member’s claimsubmission until reimbursement. The results are shown in Table 9.Bills were paid within one month on average. Considering that the CC meets once a month

and that the IA needs to visit villages to collect claims and prepare them for decisions, and

0%

20%

40%

60%

80%

100%

120%

0

50

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% c

laim

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.y)

Hospital Benefit at different caps (p.p.p.y)

Premium % claims fully covered

2000 4000 6000 8000 10000 12000 14000

Figure 4. Coverage levels at different caps/hospitalisations (Banke).

Table 9 Promptness of claims reimbursement

Scheme district Enrolmentperiod

Batchcovered(months)

# Days fromsubmission toCC decision

# Days fromCC decisionto payment

# Days fromsubmission to

payment

Mean± SEM Mean± SEM Mean± SEM

Saubhagya Dhading January 2011 12 14± 0.98 15± 0.72 28± 1.08July 2011 12 10± 0.80 12± 0.44 23± 0.85January 2012 10 10± 0.42 11± 0.22 21± 0.48July 2012 4 11± 0.95 12± 0.48 24± 1.21

Sanjeevni Banke June 2011 12 13± 0.35 11± 0.27 24± 0.42June 2012 5 13± 0.38 10± 0.18 24± 0.46

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that cash payments are made to members at doorstep, the promptness of the process seemsremarkable. Promptness could hardly improve if payments should continue to be madethrough personal interaction at doorstep, recalling the objective difficulties of travelling toremote villages and the scarce number of CBHI staff.

Discussion

This paper describes the implementation of two contributory, voluntary, context-adapted anddemand-driven health insurance schemes in rural Nepal. The two locations differ from eachother in many ways: Dhading is hilly whereas Banke is in the plain; Banke is relativelypoorer in terms of MPCC, but has more availability of health-care providers. The differenceswere also reflected in the choice of benefit package. Owing to these reasons, instead ofcombining the results of two districts, we preferred to show them separately. Thesedifferences notwithstanding, the implementation of CBHI in both locations has beensuccessful. The implementation model is founded on a partnership model (where all partiesget a share of the productivity gains from pooling) through the application of the followingcomponents: (i) trusted governance at local level; mobilising local rules-in-use and localstaff to manage the mutual model with no or few conflicts of interests typical to insurance;(ii) combining “awareness chain” (affiliation-enhancing insurance literacy32 with a “valuechain” (comprehensible value proposition of insurance) and with a “competence chain”(capacity development of local persons); (iii) context-relevance in pricing and priority-setting of the risks covered, enabling both a contextualised rationing of partial benefits andgaining credibility by involving prospective enrollees in design and pricing.The unique feature of this implementation model is its design to achieve three objectives:

(i) enabling target communities to take decisions that affect their members’ lives (in context,this means deciding on the composition of their benefit package and its price); (ii) enablingcommunities to be in control of the money paid by members to the CBHI (to reduce concernsabout leakages, fraud or corruption); and (iii) enabling communities to control that the pre-defined rules of the game are followed (in context, this means local governance of dailyoperations of the insurance). The following five critical conditions serve as benchmarks toreview the success of the schemes in achieving these objectives.

The coverage should deal with risks of the insured

This condition means covering risks that the target group prioritises. The dialog with thetarget population on rationing, WTP and priority-setting must be based on local risk-exposure, that is, morbidity, provision and health-care costs. The data (Tables 6 and 7)demonstrate significant differences across the two locations, a situation already reported inother contexts.33 The external change maker was responsible for structuring data acquisitionand calculating premiums for different benefit options (a role requiring statistical andactuarial expertise), and the target community provided the information and then took thelead in making choices. The benefits (e.g. hospitalisation, imaging, lab tests, wage loss,

32 Panda et al. (2013).33 Dror et al. (2008).

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transportation, etc.) were chosen in two stages, first (rough cut) by community leaders,followed by a selection by small groups; the package selected by most groups was thenretained as the one package applying to all. This interactive process of involving prospectiveinsureds in package design, while time-consuming and labour-intensive, increased thepopulation’s understanding about the insurance. The “design workshop” (renamed “redesignworkshop” when repeated the following year) enabled insured members to modify theirchoices based on their actual experience. For example, in Dhading in Year 2, membersdecided to increase the imaging cap from NPR 500 to 600 and in Banke, from NPR 250 to600 (Table 2). It is noteworthy that in both schemes and in both years, the outpatient benefitsincluded represented about half the premium cost (e.g. lab tests and imaging; premiumdata not shown). This package composition differs considerably from what most commercialschemes cover (only inpatient care). Recalling that low enrolment among commercial“microinsurance” schemes was due to the limited coverage of outpatient care,34 the involve-ment of CBHI members in package design in these schemes led to a different priority-setting.

The price should be affordable

Affordability is what each target group considers as the acceptable price for its unique variantof health insurance. We assessed this by obtaining two estimates of WTP, one by applying a“descending bidding game” (one method of contingent valuation) as part of data collection,and the second by applying a novel alternative method to proxy WTP for health insurance asan estimated 4.5 per cent of mean food expenditure.27 The premiums presented to the targetgroups in the design workshops were between these two estimates of WTP (see Figures 1and 2). The members chose benefit packages that commanded premiums closer to the higherWTP estimate (premiums were NPR 26.2 and 28 in Dhading, and NPR 20 and 35 in Banke,respectively for the first and second enrolment periods; upper and lower WTP estimates wereNPR 41 and NPR 10 pppm in Dhading; and NPR 38 and 10.46 pppm in Banke). We thinkthat the lively group discussions (occasioned by involving so many community members inthe process of choice) enhanced the understanding of the trade-off between premiumspayable and the depth and width of coverage, and encouraged agreement to pay higherpremiums in both schemes in the second year. This could suggest that WTP increases whenthe insured population gains useful experience with insurance over time (but the effect is notuniform). It is also noted that the premiums chosen in both locations even in Year 2 are lowerthan the highest estimate of WTP.Another aspect of affordability is that administrative costs did not include profits to

intermediaries or underwriters.

The value proposition of insurance should be positive and clear

We consider membership numbers (new and renewals, Table 4) as a strong indicator of apositive perception of the value proposition by the target population. In Dhading, member-ship rose from 514 to 2,060 (+300 per cent) in July 2012 and to 3,363 (+ 554 per cent) by endJanuary 2013, and in Banke the membership rose from 4,176 in Year 1 to 7,881 in Year 2(+90 per cent). Renewals were voluntary, and rates were around 66 per cent in Dhading and

34 Pott and Holtz (2013).

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49.4 per cent in Banke; there is scope for improvement. The household size of the targetpopulation was much larger than the average size of insured households (5.2 vs 2.9 lives inDhading, and 5.6 vs 2.4 in Banke). The insured members (SRG women) did not avail of theopportunity to insure all their household members; the under-6 young girls were under-represented (Table 5). The traditional hierarchy in allocating resources within the family(lower allocation to girl children) is reflected in this context of considering the valueproposition of insurance. Changing this perception will require more group discussions.Another aspect of the value proposition of insurance is the share of premiums paid back to

members (loss ratio); these ratios are of course very sensitive to caps, and the increases ofcaps for outpatient services that were adopted in Year 2 suggest that the target populationfully understood this relationship. Finally, prompt reimbursement added to the sense ofvalue, as members were less exposed to secure interim financing through loans.

The process is transparent and trusted by the insured

The transparency of the business process was enhanced by placing the operations of thescheme in the hands of members chosen by other members for their posts. Putting theoperation and governance in the hands of members (formally a mutual-aid model) removessome conflicts of interest that exist in the partner-agent model, provided that the managers ofthe scheme run it well. The symbiosis between communities (the decision-makers) and theexternal facilitator (the change maker) made it possible to deliver tailored training to trustedofficials that the community chose so that they would perform effectively, efficiently andlocally. The training costs are not paid by the community, and the capacity-developmentactivities are an essential part of this implementation model. The operative assumptionunderlying the inclusion of a “competencies chain” in the implementation model is that, withtime, increased autonomy and self-reliance of communities in running their insuranceschemes will allow the phasing out of technical assistance. And the development assumptionis that the front-loaded costs in developing local capacity is a justified and essential phasetowards achieving the development goals of better access to health care by rural people.

Viable supply and solvent demand could be established

The reports of other (micro) health insurance projects in Nepal (referenced earlier) suggestseveral unsuccessful attempts, even with external subsidies. The remarkable achievementreported here is that in similar terrain and difficult conditions, two rural communities,composed mostly of poor persons with low education and no prior exposure to healthinsurance, succeeded in organising and paying for a viable supply of health insurance whereno (commercial) insurer was willing to underwrite risk. Moreover, they did this by respectinga perfect match between local solvent demand, and local prioritisation of benefits. Thirdly,the communities demonstrated their ability to govern a scheme transparently and respon-sibly. The net result was that the communities used new competencies to consolidate all theconditions to establish and operate a market for health insurance benefitting all concernedwhere none existed before. The implementation model does not entail any subsidy topremiums, yet operations have been sustainable and have grown from year to year. Thetechnical and actuarial advice provided to the communities during the inception years wasessential in ensuring viable insurance operations. These costs are in fact development costs,

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to create a nascent market for health insurance; they cannot and should not be borne by therural poor, protagonists of this development. In passing, we add that the costs are lower thanbenchmarks for operating health insurance in other settings.This study is subject to certain limitations as well. For one, this study described the

successful operation of two stand-alone CBHIs. Previous studies flagged that small stand-alone schemes could have solvency issues.35 The Nepali CBHIs are, of course, exposed tothis risk as well. The solution could be creating a mutual reinsurance fund to pool outlierrisks. That option might be politically more pertinent when more people become insured byCBHIs. Secondly, the analysis of the outcome is using claims data of the first full year, butthe first year may differ from subsequent years.

Conclusions

The argument has been made that poor people demand a development process driven by theircommunities.36 This article provides empirical evidence of the development of healthinsurance driven by the beneficiary communities in rural Nepal.After more than two years of operation, the CBHI schemes have been successful in

retaining many/most enrollees beyond the original one-year contract and in attracting manynew enrollees. This was achieved without premium subsidies and on a voluntary basis, asmembers agreed to pay health insurance premiums. From a development perspective, this isa remarkable and rare demonstration that contributory health insurance without premiumsubsidies can be attractive to rural poor in a low-income country. It is also a demonstrationthat when the target population is involved in priority-setting and pricing, partial coverageis financially and administratively possible. This voluntary, contributory, needs-basedand demand-driven implementation model met with a very good response at the grassrootslevel, and responds to the wishes of the communities to retain decisions, funds, priorities andoperations locally. The experience offers evidence of success in overcoming the single mostchallenging obstacle to UHC in the informal sector in low-income countries, namely,generating contributions from rural poor populations.This positive evaluation notwithstanding, the verdict is still out whether these CBHI

schemes can keep a similar score in the long term. This is similar to the question, on manyminds, whether the unknown sportsman that hit a new record is the new champion, or maybejust the one-off lucky beginner. The undisputed facts are the positive results posted and thesmall-scale size of these implementations. Can this model be replicated to provide healthinsurance coverage to the majority of the Nepalese population living on less than $2 per day?The answer is unclear at this stage, mainly because scaling will require financial resources toprovide technical assistance to enable communities become the decision-makers and marketmakers. The social change of bringing rural persons to manage mutual insurance is notintuitive, and birthing it must be funded as development aid, not as administrative loading.Considering that the Government of Nepal intends to reach UHC and must generateresources through contributions from the beneficiaries, we submit and conclude that the

35 Dror and Armstrong (2006).36 Narayan et al. (2000).

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CBHI model described here could make a definite contribution to achieving social policygoals of Nepal.

Acknowledgements

The authors gratefully acknowledge the financial, technical and administrative support without whichthis study could not have been carried out, including: funding by Rockefeller Foundation New York37

(grant No. 2008 PHS 229 to Prof. David Dror via Erasmus University Rotterdam) and a grant from ananonymous donor to Save the Children USA (sub-grant #31531-01) to complete the baseline study(development of questionnaires, data collection and cleaning, analysis and report writing) in 2009/2010; funding from the German Ministry of International Cooperation (BMZ) through MISEREOR(the German Catholic Bishops’ Organisation for Development Cooperation38) (grant No. 323-900-1098ZG, 2011) to support the costs of initiating, involving, launching and operating the schemes during2010–2012, as well as the cost of Open Access publication. The Micro Insurance Academy has beenproviding steering, ongoing technical, statistical and other assistance to the CBHI project and to fieldpartners at all the stages. Mr. Ralf Radermacher of MIA led the initial development stages; Ms. DhritiBhatta and later Mr. Vikram Patil (MIA staff) provided backstopping and project management of theimplementation process. Save the Children (Nepal Country Office) provided logistical support; Dr.Harihar Dev Pant, Chairman of Nirdhan Utthan Bank Ltd and his team in Nepalganj branch, Banke, aswell as Mr. Kailash Rijal, Deputy Director of DEPROSC and his team in Dhading, the field partners,were instrumental in securing the cooperation of the members and their field staff. Dr. Lucy Firth (leadeconomist, MIA) offered insightful in-house editorial peer-review before submission for publication.Two anonymous peer reviewers also offered useful comments. Thanks to all.

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Figure A1. Details of the MIA implementation process.

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Figure B1. CHAT board describing various benefit packages, prepared by MIA.

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About the Authors

David M. Dror, PhD, DBA, is the Chairman of the Micro Insurance Academy andHonorary Professor at Institute of Health Policy and Management, Erasmus UniversityRotterdam.

Atanu MajumdarMSc, a Statistician, is Senior Research Consultant at the Micro InsuranceAcademy (MIA), India.

Pradeep Panda, PhD, an Economist and a Demographer, is Director of Research at theMicro Insurance Academy (MIA), India.

Denny John, MPH, is Deputy Director of Implementation at the Micro Insurance Academy(MIA), India.

Ruth Koren PhD is a Professor at Tel Aviv University Medical School, Israel.

This work is licensed under a Creative Commons Attribution 3.0 UnportedLicense. To view a copy of this license, visit http://creativecommons.org/

licenses/by/3.0/

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